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        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

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        About MultiQC

        This report was generated using MultiQC, version 1.15

        You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

        For more information about MultiQC, including other videos and extensive documentation, please visit http://multiqc.info

        You can report bugs, suggest improvements and find the source code for MultiQC on GitHub: https://github.com/ewels/MultiQC

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2025-10-01, 12:37 PDT based on data in: /mmfs1/gscratch/srlab/ashuff/moorea-2023-rnaseq/trimmed-sequences


        General Statistics

        Showing 254/254 rows and 3/6 columns.
        Sample Name% Dups% GCM Seqs
        trim.10_S131_R1_001
        39.8%
        42%
        2.6
        trim.10_S131_R2_001
        36.5%
        42%
        2.6
        trim.10_S921_R1_001
        48.6%
        42%
        7.5
        trim.10_S921_R2_001
        44.9%
        42%
        7.5
        trim.11_S132_R1_001
        57.5%
        42%
        24.4
        trim.11_S132_R2_001
        53.3%
        42%
        24.4
        trim.11_S922_R1_001
        3.3%
        42%
        0.0
        trim.11_S922_R2_001
        3.0%
        42%
        0.0
        trim.12_S133_R1_001
        60.6%
        42%
        3.3
        trim.12_S133_R2_001
        58.1%
        43%
        3.3
        trim.12_S923_R1_001
        75.3%
        42%
        9.7
        trim.12_S923_R2_001
        73.9%
        42%
        9.7
        trim.13_S134_R1_001
        32.0%
        42%
        3.5
        trim.13_S134_R2_001
        29.2%
        42%
        3.5
        trim.13_S924_R1_001
        37.7%
        42%
        9.8
        trim.13_S924_R2_001
        34.4%
        42%
        9.8
        trim.14_S135_R1_001
        40.3%
        42%
        4.7
        trim.14_S135_R2_001
        35.4%
        43%
        4.7
        trim.14_S925_R1_001
        48.4%
        43%
        12.9
        trim.14_S925_R2_001
        43.4%
        43%
        12.9
        trim.15_S136_R1_001
        39.3%
        42%
        3.8
        trim.15_S136_R2_001
        35.8%
        42%
        3.8
        trim.15_S926_R1_001
        47.5%
        42%
        10.2
        trim.15_S926_R2_001
        43.3%
        42%
        10.2
        trim.16_S137_R1_001
        43.8%
        41%
        3.5
        trim.16_S137_R2_001
        40.2%
        41%
        3.5
        trim.16_S927_R1_001
        53.5%
        41%
        9.9
        trim.16_S927_R2_001
        50.3%
        41%
        9.9
        trim.17_S138_R1_001
        38.5%
        41%
        4.2
        trim.17_S138_R2_001
        33.6%
        41%
        4.2
        trim.17_S928_R1_001
        46.5%
        41%
        11.3
        trim.17_S928_R2_001
        41.8%
        41%
        11.3
        trim.18_S139_R1_001
        45.1%
        41%
        3.0
        trim.18_S139_R2_001
        41.9%
        41%
        3.0
        trim.18_S929_R1_001
        55.4%
        41%
        7.9
        trim.18_S929_R2_001
        52.6%
        41%
        7.9
        trim.19_S140_R1_001
        36.0%
        43%
        3.8
        trim.19_S140_R2_001
        33.1%
        43%
        3.8
        trim.19_S930_R1_001
        42.6%
        43%
        9.2
        trim.19_S930_R2_001
        39.1%
        43%
        9.2
        trim.1_S122_R1_001
        41.4%
        41%
        3.5
        trim.1_S122_R2_001
        37.6%
        41%
        3.5
        trim.1_S912_R1_001
        49.4%
        41%
        9.2
        trim.1_S912_R2_001
        45.9%
        41%
        9.2
        trim.20_S141_R1_001
        41.4%
        42%
        4.5
        trim.20_S141_R2_001
        37.2%
        42%
        4.5
        trim.20_S931_R1_001
        49.4%
        42%
        11.6
        trim.20_S931_R2_001
        45.5%
        42%
        11.6
        trim.21_S142_R1_001
        39.9%
        41%
        3.4
        trim.21_S142_R2_001
        36.1%
        42%
        3.4
        trim.21_S932_R1_001
        47.5%
        42%
        9.2
        trim.21_S932_R2_001
        43.7%
        42%
        9.2
        trim.22_S143_R1_001
        40.5%
        42%
        3.1
        trim.22_S143_R2_001
        37.9%
        42%
        3.1
        trim.22_S933_R1_001
        48.6%
        42%
        8.5
        trim.22_S933_R2_001
        45.9%
        42%
        8.5
        trim.23_S144_R1_001
        33.6%
        42%
        2.9
        trim.23_S144_R2_001
        28.9%
        42%
        2.9
        trim.23_S934_R1_001
        43.6%
        42%
        9.0
        trim.23_S934_R2_001
        38.6%
        42%
        9.0
        trim.24_S145_R1_001
        39.9%
        41%
        4.0
        trim.24_S145_R2_001
        37.1%
        41%
        4.0
        trim.24_S935_R1_001
        48.7%
        41%
        10.6
        trim.24_S935_R2_001
        45.5%
        41%
        10.6
        trim.25_S146_R1_001
        44.9%
        41%
        3.3
        trim.25_S146_R2_001
        40.8%
        42%
        3.3
        trim.25_S936_R1_001
        58.2%
        41%
        9.6
        trim.25_S936_R2_001
        54.8%
        42%
        9.6
        trim.26_S147_R1_001
        37.3%
        42%
        3.9
        trim.26_S147_R2_001
        34.2%
        42%
        3.9
        trim.26_S937_R1_001
        45.5%
        42%
        10.5
        trim.26_S937_R2_001
        42.0%
        42%
        10.5
        trim.27_S148_R1_001
        37.4%
        42%
        4.2
        trim.27_S148_R2_001
        33.1%
        42%
        4.2
        trim.27_S938_R1_001
        45.8%
        42%
        11.1
        trim.27_S938_R2_001
        41.6%
        42%
        11.1
        trim.28_S149_R1_001
        34.1%
        43%
        3.8
        trim.28_S149_R2_001
        29.6%
        43%
        3.8
        trim.28_S939_R1_001
        43.1%
        43%
        10.7
        trim.28_S939_R2_001
        38.6%
        43%
        10.7
        trim.29_S150_R1_001
        38.5%
        42%
        4.4
        trim.29_S150_R2_001
        34.5%
        43%
        4.4
        trim.29_S940_R1_001
        47.7%
        42%
        12.3
        trim.29_S940_R2_001
        44.1%
        43%
        12.3
        trim.2_S123_R1_001
        38.2%
        43%
        4.0
        trim.2_S123_R2_001
        34.5%
        44%
        4.0
        trim.2_S913_R1_001
        47.3%
        43%
        10.7
        trim.2_S913_R2_001
        43.7%
        44%
        10.7
        trim.30_S151_R1_001
        49.0%
        42%
        8.4
        trim.30_S151_R2_001
        46.4%
        42%
        8.4
        trim.30_S941_R1_001
        59.0%
        42%
        23.0
        trim.30_S941_R2_001
        56.6%
        42%
        23.0
        trim.31_S152_R1_001
        38.9%
        41%
        4.4
        trim.31_S152_R2_001
        34.1%
        41%
        4.4
        trim.31_S942_R1_001
        47.9%
        41%
        12.4
        trim.31_S942_R2_001
        43.1%
        41%
        12.4
        trim.32_S153_R1_001
        40.9%
        42%
        4.3
        trim.32_S153_R2_001
        37.3%
        43%
        4.3
        trim.32_S943_R1_001
        49.8%
        42%
        11.4
        trim.32_S943_R2_001
        46.6%
        43%
        11.4
        trim.33_S154_R1_001
        37.7%
        42%
        3.8
        trim.33_S154_R2_001
        33.4%
        42%
        3.8
        trim.33_S944_R1_001
        46.0%
        42%
        10.5
        trim.33_S944_R2_001
        41.6%
        42%
        10.5
        trim.34_S155_R1_001
        40.7%
        42%
        3.8
        trim.34_S155_R2_001
        38.5%
        42%
        3.8
        trim.34_S945_R1_001
        47.9%
        42%
        9.6
        trim.34_S945_R2_001
        45.3%
        42%
        9.6
        trim.35_S156_R1_001
        37.3%
        42%
        3.8
        trim.35_S156_R2_001
        33.2%
        43%
        3.8
        trim.35_S946_R1_001
        45.5%
        43%
        10.2
        trim.35_S946_R2_001
        41.1%
        43%
        10.2
        trim.36_S157_R1_001
        40.3%
        42%
        4.8
        trim.36_S157_R2_001
        35.0%
        42%
        4.8
        trim.36_S947_R1_001
        48.5%
        42%
        12.2
        trim.36_S947_R2_001
        43.4%
        42%
        12.2
        trim.37_S158_R1_001
        38.5%
        41%
        3.8
        trim.37_S158_R2_001
        36.6%
        42%
        3.8
        trim.37_S948_R1_001
        45.5%
        42%
        9.5
        trim.37_S948_R2_001
        43.7%
        42%
        9.5
        trim.38_S159_R1_001
        59.6%
        42%
        25.2
        trim.38_S159_R2_001
        57.6%
        42%
        25.2
        trim.38_S949_R1_001
        0.0%
        44%
        0.0
        trim.38_S949_R2_001
        0.0%
        41%
        0.0
        trim.39_S160_R1_001
        38.7%
        41%
        2.7
        trim.39_S160_R2_001
        36.1%
        41%
        2.7
        trim.39_S950_R1_001
        49.2%
        41%
        8.6
        trim.39_S950_R2_001
        46.7%
        41%
        8.6
        trim.3_S124_R1_001
        40.8%
        41%
        4.0
        trim.3_S124_R2_001
        38.2%
        41%
        4.0
        trim.3_S914_R1_001
        48.4%
        41%
        9.9
        trim.3_S914_R2_001
        45.9%
        42%
        9.9
        trim.40_S161_R1_001
        41.4%
        41%
        4.3
        trim.40_S161_R2_001
        39.0%
        42%
        4.3
        trim.40_S951_R1_001
        50.0%
        41%
        11.0
        trim.40_S951_R2_001
        48.0%
        42%
        11.0
        trim.41_S162_R1_001
        38.2%
        41%
        3.4
        trim.41_S162_R2_001
        35.2%
        41%
        3.4
        trim.41_S952_R1_001
        46.0%
        41%
        8.9
        trim.41_S952_R2_001
        43.0%
        41%
        8.9
        trim.42_S163_R1_001
        43.8%
        43%
        4.7
        trim.42_S163_R2_001
        38.9%
        43%
        4.7
        trim.42_S953_R1_001
        52.9%
        43%
        13.0
        trim.42_S953_R2_001
        48.3%
        43%
        13.0
        trim.43_S164_R1_001
        35.7%
        42%
        4.1
        trim.43_S164_R2_001
        31.9%
        42%
        4.1
        trim.43_S954_R1_001
        42.5%
        42%
        10.3
        trim.43_S954_R2_001
        38.6%
        42%
        10.3
        trim.44_S165_R1_001
        36.6%
        43%
        3.7
        trim.44_S165_R2_001
        33.1%
        43%
        3.7
        trim.44_S955_R1_001
        44.9%
        43%
        9.9
        trim.44_S955_R2_001
        41.5%
        43%
        9.9
        trim.45_S166_R1_001
        45.2%
        41%
        3.9
        trim.45_S166_R2_001
        42.5%
        42%
        3.9
        trim.45_S956_R1_001
        54.2%
        41%
        10.5
        trim.45_S956_R2_001
        51.9%
        42%
        10.5
        trim.46_S167_R1_001
        31.6%
        45%
        3.5
        trim.46_S167_R2_001
        28.7%
        45%
        3.5
        trim.46_S957_R1_001
        40.1%
        45%
        9.7
        trim.46_S957_R2_001
        36.6%
        45%
        9.7
        trim.47_S168_R1_001
        36.6%
        42%
        4.3
        trim.47_S168_R2_001
        32.4%
        42%
        4.3
        trim.47_S958_R1_001
        45.0%
        42%
        11.6
        trim.47_S958_R2_001
        40.6%
        42%
        11.6
        trim.48_S169_R1_001
        39.5%
        41%
        4.7
        trim.48_S169_R2_001
        35.0%
        42%
        4.7
        trim.48_S959_R1_001
        48.5%
        41%
        12.9
        trim.48_S959_R2_001
        44.3%
        42%
        12.9
        trim.49_S170_R1_001
        36.1%
        43%
        3.6
        trim.49_S170_R2_001
        33.8%
        43%
        3.6
        trim.49_S960_R1_001
        43.2%
        43%
        9.5
        trim.49_S960_R2_001
        40.5%
        43%
        9.5
        trim.4_S125_R1_001
        51.6%
        41%
        4.8
        trim.4_S125_R2_001
        46.6%
        41%
        4.8
        trim.4_S915_R1_001
        60.9%
        41%
        12.6
        trim.4_S915_R2_001
        56.4%
        41%
        12.6
        trim.50_S171_R1_001
        39.3%
        43%
        3.9
        trim.50_S171_R2_001
        35.5%
        43%
        3.9
        trim.50_S961_R1_001
        47.9%
        43%
        11.0
        trim.50_S961_R2_001
        44.0%
        43%
        11.0
        trim.51_S172_R1_001
        37.7%
        42%
        3.9
        trim.51_S172_R2_001
        35.5%
        43%
        3.9
        trim.51_S962_R1_001
        44.5%
        43%
        9.9
        trim.51_S962_R2_001
        41.9%
        43%
        9.9
        trim.52_S173_R1_001
        37.0%
        42%
        3.8
        trim.52_S173_R2_001
        34.6%
        42%
        3.8
        trim.52_S963_R1_001
        43.6%
        42%
        9.3
        trim.52_S963_R2_001
        41.0%
        43%
        9.3
        trim.53_S174_R1_001
        38.1%
        42%
        4.3
        trim.53_S174_R2_001
        34.9%
        43%
        4.3
        trim.53_S964_R1_001
        46.5%
        42%
        11.1
        trim.53_S964_R2_001
        42.9%
        43%
        11.1
        trim.54_S175_R1_001
        57.7%
        43%
        23.0
        trim.54_S175_R2_001
        54.5%
        43%
        23.0
        trim.55_S176_R1_001
        38.1%
        41%
        4.2
        trim.55_S176_R2_001
        33.7%
        41%
        4.2
        trim.55_S966_R1_001
        46.5%
        41%
        11.3
        trim.55_S966_R2_001
        42.1%
        41%
        11.3
        trim.56_S177_R1_001
        40.8%
        41%
        3.9
        trim.56_S177_R2_001
        38.2%
        41%
        3.9
        trim.56_S967_R1_001
        49.8%
        41%
        10.8
        trim.56_S967_R2_001
        47.3%
        41%
        10.8
        trim.57_S178_R1_001
        37.3%
        42%
        4.2
        trim.57_S178_R2_001
        33.6%
        42%
        4.2
        trim.57_S968_R1_001
        45.0%
        42%
        11.6
        trim.57_S968_R2_001
        41.0%
        42%
        11.6
        trim.58_S179_R1_001
        21.4%
        42%
        6.2
        trim.58_S179_R2_001
        19.6%
        42%
        6.2
        trim.58_S969_R1_001
        26.6%
        42%
        17.0
        trim.58_S969_R2_001
        24.7%
        42%
        17.0
        trim.59_S180_R1_001
        37.2%
        42%
        3.8
        trim.59_S180_R2_001
        32.9%
        42%
        3.8
        trim.59_S970_R1_001
        45.2%
        42%
        10.0
        trim.59_S970_R2_001
        40.7%
        42%
        10.0
        trim.5_S126_R1_001
        44.0%
        42%
        4.5
        trim.5_S126_R2_001
        41.5%
        42%
        4.5
        trim.5_S916_R1_001
        50.9%
        42%
        10.9
        trim.5_S916_R2_001
        48.3%
        42%
        10.9
        trim.60_S181_R1_001
        39.7%
        41%
        3.7
        trim.60_S181_R2_001
        37.0%
        41%
        3.7
        trim.60_S971_R1_001
        48.1%
        41%
        10.2
        trim.60_S971_R2_001
        45.4%
        41%
        10.2
        trim.61_S182_R1_001
        27.7%
        43%
        1.7
        trim.61_S182_R2_001
        23.9%
        43%
        1.7
        trim.61_S972_R1_001
        34.1%
        43%
        4.5
        trim.61_S972_R2_001
        29.6%
        43%
        4.5
        trim.62_S183_R1_001
        34.9%
        41%
        3.9
        trim.62_S183_R2_001
        30.4%
        42%
        3.9
        trim.62_S973_R1_001
        43.2%
        42%
        10.3
        trim.62_S973_R2_001
        38.8%
        42%
        10.3
        trim.63_S184_R1_001
        37.9%
        41%
        3.3
        trim.63_S184_R2_001
        35.1%
        41%
        3.3
        trim.63_S974_R1_001
        46.4%
        41%
        9.2
        trim.63_S974_R2_001
        43.5%
        41%
        9.2
        trim.64_S185_R1_001
        46.4%
        41%
        3.8
        trim.64_S185_R2_001
        42.0%
        41%
        3.8
        trim.64_S975_R1_001
        56.0%
        41%
        10.4
        trim.64_S975_R2_001
        52.4%
        41%
        10.4
        trim.6_S127_R1_001
        43.7%
        42%
        4.1
        trim.6_S127_R2_001
        38.5%
        43%
        4.1
        trim.6_S917_R1_001
        53.4%
        42%
        11.0
        trim.6_S917_R2_001
        48.4%
        43%
        11.0
        trim.7_S128_R1_001
        34.7%
        44%
        4.3
        trim.7_S128_R2_001
        31.3%
        45%
        4.3
        trim.7_S918_R1_001
        41.9%
        44%
        11.4
        trim.7_S918_R2_001
        38.0%
        45%
        11.4
        trim.8_S129_R1_001
        40.1%
        42%
        4.4
        trim.8_S129_R2_001
        37.0%
        42%
        4.4
        trim.8_S919_R1_001
        48.9%
        42%
        12.4
        trim.8_S919_R2_001
        45.8%
        42%
        12.4
        trim.9_S130_R1_001
        40.9%
        41%
        5.4
        trim.9_S130_R2_001
        37.0%
        41%
        5.4
        trim.9_S920_R1_001
        47.8%
        41%
        13.3
        trim.9_S920_R2_001
        43.8%
        41%
        13.3

        FastQC

        FastQC is a quality control tool for high throughput sequence data, written by Simon Andrews at the Babraham Institute in Cambridge.

        Sequence Counts

        Sequence counts for each sample. Duplicate read counts are an estimate only.

        This plot show the total number of reads, broken down into unique and duplicate if possible (only more recent versions of FastQC give duplicate info).

        You can read more about duplicate calculation in the FastQC documentation. A small part has been copied here for convenience:

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Sequence Quality Histograms

        The mean quality value across each base position in the read.

        To enable multiple samples to be plotted on the same graph, only the mean quality scores are plotted (unlike the box plots seen in FastQC reports).

        Taken from the FastQC help:

        The y-axis on the graph shows the quality scores. The higher the score, the better the base call. The background of the graph divides the y axis into very good quality calls (green), calls of reasonable quality (orange), and calls of poor quality (red). The quality of calls on most platforms will degrade as the run progresses, so it is common to see base calls falling into the orange area towards the end of a read.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Per Sequence Quality Scores

        The number of reads with average quality scores. Shows if a subset of reads has poor quality.

        From the FastQC help:

        The per sequence quality score report allows you to see if a subset of your sequences have universally low quality values. It is often the case that a subset of sequences will have universally poor quality, however these should represent only a small percentage of the total sequences.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Per Base Sequence Content

        The proportion of each base position for which each of the four normal DNA bases has been called.

        To enable multiple samples to be shown in a single plot, the base composition data is shown as a heatmap. The colours represent the balance between the four bases: an even distribution should give an even muddy brown colour. Hover over the plot to see the percentage of the four bases under the cursor.

        To see the data as a line plot, as in the original FastQC graph, click on a sample track.

        From the FastQC help:

        Per Base Sequence Content plots out the proportion of each base position in a file for which each of the four normal DNA bases has been called.

        In a random library you would expect that there would be little to no difference between the different bases of a sequence run, so the lines in this plot should run parallel with each other. The relative amount of each base should reflect the overall amount of these bases in your genome, but in any case they should not be hugely imbalanced from each other.

        It's worth noting that some types of library will always produce biased sequence composition, normally at the start of the read. Libraries produced by priming using random hexamers (including nearly all RNA-Seq libraries) and those which were fragmented using transposases inherit an intrinsic bias in the positions at which reads start. This bias does not concern an absolute sequence, but instead provides enrichement of a number of different K-mers at the 5' end of the reads. Whilst this is a true technical bias, it isn't something which can be corrected by trimming and in most cases doesn't seem to adversely affect the downstream analysis.

        Click a sample row to see a line plot for that dataset.
        Rollover for sample name
        Position: -
        %T: -
        %C: -
        %A: -
        %G: -

        Per Sequence GC Content

        The average GC content of reads. Normal random library typically have a roughly normal distribution of GC content.

        From the FastQC help:

        This module measures the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.

        In a normal random library you would expect to see a roughly normal distribution of GC content where the central peak corresponds to the overall GC content of the underlying genome. Since we don't know the the GC content of the genome the modal GC content is calculated from the observed data and used to build a reference distribution.

        An unusually shaped distribution could indicate a contaminated library or some other kinds of biased subset. A normal distribution which is shifted indicates some systematic bias which is independent of base position. If there is a systematic bias which creates a shifted normal distribution then this won't be flagged as an error by the module since it doesn't know what your genome's GC content should be.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Per Base N Content

        The percentage of base calls at each position for which an N was called.

        From the FastQC help:

        If a sequencer is unable to make a base call with sufficient confidence then it will normally substitute an N rather than a conventional base call. This graph shows the percentage of base calls at each position for which an N was called.

        It's not unusual to see a very low proportion of Ns appearing in a sequence, especially nearer the end of a sequence. However, if this proportion rises above a few percent it suggests that the analysis pipeline was unable to interpret the data well enough to make valid base calls.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Sequence Length Distribution

        The distribution of fragment sizes (read lengths) found. See the FastQC help

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Sequence Duplication Levels

        The relative level of duplication found for every sequence.

        From the FastQC Help:

        In a diverse library most sequences will occur only once in the final set. A low level of duplication may indicate a very high level of coverage of the target sequence, but a high level of duplication is more likely to indicate some kind of enrichment bias (eg PCR over amplification). This graph shows the degree of duplication for every sequence in a library: the relative number of sequences with different degrees of duplication.

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        In a properly diverse library most sequences should fall into the far left of the plot in both the red and blue lines. A general level of enrichment, indicating broad oversequencing in the library will tend to flatten the lines, lowering the low end and generally raising other categories. More specific enrichments of subsets, or the presence of low complexity contaminants will tend to produce spikes towards the right of the plot.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Overrepresented sequences

        The total amount of overrepresented sequences found in each library.

        FastQC calculates and lists overrepresented sequences in FastQ files. It would not be possible to show this for all samples in a MultiQC report, so instead this plot shows the number of sequences categorized as over represented.

        Sometimes, a single sequence may account for a large number of reads in a dataset. To show this, the bars are split into two: the first shows the overrepresented reads that come from the single most common sequence. The second shows the total count from all remaining overrepresented sequences.

        From the FastQC Help:

        A normal high-throughput library will contain a diverse set of sequences, with no individual sequence making up a tiny fraction of the whole. Finding that a single sequence is very overrepresented in the set either means that it is highly biologically significant, or indicates that the library is contaminated, or not as diverse as you expected.

        FastQC lists all of the sequences which make up more than 0.1% of the total. To conserve memory only sequences which appear in the first 100,000 sequences are tracked to the end of the file. It is therefore possible that a sequence which is overrepresented but doesn't appear at the start of the file for some reason could be missed by this module.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Adapter Content

        The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position.

        Note that only samples with ≥ 0.1% adapter contamination are shown.

        There may be several lines per sample, as one is shown for each adapter detected in the file.

        From the FastQC Help:

        The plot shows a cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. Once a sequence has been seen in a read it is counted as being present right through to the end of the read so the percentages you see will only increase as the read length goes on.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Status Checks

        Status for each FastQC section showing whether results seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        FastQC assigns a status for each section of the report. These give a quick evaluation of whether the results of the analysis seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        It is important to stress that although the analysis results appear to give a pass/fail result, these evaluations must be taken in the context of what you expect from your library. A 'normal' sample as far as FastQC is concerned is random and diverse. Some experiments may be expected to produce libraries which are biased in particular ways. You should treat the summary evaluations therefore as pointers to where you should concentrate your attention and understand why your library may not look random and diverse.

        Specific guidance on how to interpret the output of each module can be found in the relevant report section, or in the FastQC help.

        In this heatmap, we summarise all of these into a single heatmap for a quick overview. Note that not all FastQC sections have plots in MultiQC reports, but all status checks are shown in this heatmap.

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